Preparation of three-atom GHZ states based on deep reinforcement learning

DOI10.1007/s11128-021-03172-3OpenAlexW3185548723MaRDI QIDQ2690543

Liang Qiu, Guanghao Xue

Publication date: 17 March 2023

Published in: Quantum Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11128-021-03172-3

zbMATH Keywords

Greenberger-Horne-Zeilinger statestimulated Raman adiabatic passageshortcut to adiabatic passagedeep reinforcement learning

Mathematics Subject Classification ID

Computational methods for problems pertaining to quantum theory (81-08) Quantum measurement theory, state operations, state preparations (81P15)

Uses Software

• QuTiP
• Python
• TensorFlow
• OpenAI Gym
• GitHub
• Stable Baselines

Cites Work

• OpenAI Gym
• GitHub
• Generation of singlet states with Rydberg blockade mechanism and driven by adiabatic passage
• <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>N</mml:mi></mml:math>-Particle<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>N</mml
• Robust Preparation of Atomic Concatenated Greenberger–Horne–Zeilinger States via Shortcuts to Adiabaticity
• Unnamed Item
• Unnamed Item

This page was built for publication: Preparation of three-atom GHZ states based on deep reinforcement learning